The aim of this project is the development of statistical methods that either take into account interpixel correlation, or apply global image transform methods that permit an analysis of uncorrelated image components. Of typical interest is the investigation of differences between either images from individual subjects acquired under different experimental conditions, or between average images of subjects from different diagnostic groups. Three different statistical methods have been developed, based on the Fourier transform, the wavelet transform, and the theory of Gaussian random fields. In the Fourier domain, the statistics at different wave numbers are uncorrelated and inference tests can be performed unencumbered by spatial correlations. This method provides for rigorous statistical tests with well known properties and interpretations, but results in spatially uniform image blurring and may yield relatively poor spatial localization. For the wavelet-transform based analysis, a mathematically rigorous theory has been established that applies parametric statistical tests on wavelet coefficients and results in estimates of local image differences by inverse wavelet transform of only significant coefficients. The method provides for good spatial localization and the implementation of locally adaptive image smoothing, but there has not been much experience accumulated for the interpretation of test outcomes and estimates of image differences. Gaussian random field analysis has good spatial localization properties and permits the investigation of correlations with external variables (e.g., age), but it results in spatially uniform image blurring and does not provide for estimates of image differences. All three methods have been applied to the analysis of PET images from normal and alcoholic subjects and have identified significant differences in generally the same brain regions. Gaussian random field analysis was able to demonstrate in PET images from alcoholics a significant negative correlation of glucose utilization in the pre-frontal cortex with age. Wavelet-based analysis detected in functional MRI bilateral blood flow in-creases in the amygdala due to olfactory stimuli, and blood flow increases in the contralateral primary sensori-motor cortex and in focal regions in the ipsilateral cerebellum as a response to a unilateral finger tapping task.